Genet: A connectionist architecture for solving constraint satisfaction problems by iterative improvement

New approaches to solving constraint satisfaction problems using iterative improvement techniques have been found to be successful on certain, very large problems such as the million queens. However, on highly constrained problems it is possible for these methods to get caught in local minima. In this paper we present genet, a connectionist architecture for solving binary and general constraint satisfaction problems by iterative improvement. genet incorporates a learning strategy to escape from local minima. Although genet has been designed to be implemented on vlsi hardware, we present empirical evidence to show that even when simulated on a single processor genet can outperform existing iterative improvement techniques on hard instances of certain constraint satisfaction problems

Cancer stage at diagnosis: Comparison of insurance status in SEER to the Department of Defense Cancer Registry

Abstract Background Military individuals, retirees, and their families have free care or minimal out‐of‐pocket costs in the US military health system (MHS). In contrast, out‐of‐pocket costs in the US general population vary substantially. This study compared cancer patients with various insurance types in the general population to those in the MHS in cancer stage at diagnosis. Methods Patients were identified from the US Department of Defense's (DoD) Automated Central Tumor Registry (ACTUR) and the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program. Tumor stage at diagnosis of breast, prostate, lung, and colon cancers during 2007–2013 was compared between ACTUR and SEER insurance categories of “insured,” “insured‐no specifics,” “any Medicaid,” and “uninsured,” A multivariable logistic regression analysis estimated the odds ratio (OR) of late stage (Stages III and IV) versus early stage (Stages I and II) cancers comparing SEER insurance status to ACTUR. Results There were 18,440 eligible patients identified from ACTUR and 831,959 patients identified from SEER. For all cancer types, patients in the SEER‐insured/no specifics, Medicaid, and uninsured groups had significantly greater likelihood of late stage diagnosis compared to ACTUR patients. The adjusted ORs were greatest among uninsured and Medicaid patients. The SEER‐insured group also had a significantly higher odds of advanced stage disease than ACTUR patients for prostate cancer and lung cancer. Conclusion Patients in the MHS with universal access to healthcare were diagnosed at an earlier stage than those in the general population. This difference was most evident compared to Medicaid and uninsured groups

Racial disparities in histopathologic characteristics of uterine cancer are present in older, not younger blacks in an equal-access environment

Objective. We sought to determine whether racial disparities in tumor characteristics among uterine cancer patients persisted, and varied by age, in an equal-access healthcare population. Methods. The distributions of tumor histology, stage and grade by race were compared for uterine cancers diagnosed from 1990 to 2003 using data from the U.S. Department of Defense\u27s Automated Central Tumor Registry. Comparisons were conducted overall and stratified by age (\u3c50, ≥50) using the Chi-square test. Results. Of 2582 uterine tumors identified, 2057 (79.7%) were diagnosed among White women and 183 (7.1%) among Black women. Among all women analyzed, Blacks were more likely than Whites to present with non-endometrioid tumors (47.7% vs 23.5%, p\u3c0.01), non-localized tumors (31.8% vs 24.5%, p=0.02), and poorly differentiated tumors (20.5% vs 15.0%, p\u3c0.01). Among women 50 years and older, similar significant racial disparitieswere observed.However, no significant racial differenceswere observedamong young patients.When comparisons were restricted to endometrioid histology adenocarcinomas, trends in age-specific disparities for older women were observed. Conclusions. Our study suggests that racial disparities in uterine cancers persist between Blacks and Whites in an equal-access population. Blacks endure higher stage and grade tumors, and more aggressive histologies. This disparity in clinicopathologic factors is confined to women older than 50 years. Multiple factors such as racial variation in age-related health knowledge/behavior and estrogenmetabolismmay be related to the racial disparity

Relationship between Cigarette Smoking and Cancer Characteristics and Survival among Breast Cancer Patients

Carcinogenic effects of tobacco smoke may affect breast tumorigenesis. To assess whether cigarette smoking is associated with breast cancer characteristics, we investigated the relationships between smoking, pathological characteristics, and outcomes in 2153 women diagnosed with breast cancer 2001–2016. Patients were classified as never, former, or current smokers at the time of diagnosis. Logistic regression and multivariable Cox proportional hazards analysis were performed to determine whether smoking was associated with tumor characteristics. Multivariable Cox proportional hazards analysis was conducted to compare former or current smokers to never smokers in survival with adjustment for the potential confounders. The majority of women (61.8%) never smoked, followed by former smokers (26.2%) and current smokers (12.0%). After adjustment for demographic variables, body mass index, and comorbidities, tumor characteristics were not significantly associated with smoking status or pack-years smoked. Ten-year overall survival was significantly lower for former and current smokers compared to never smokers (p = 0.0105). However, breast cancer specific survival did not differ significantly between groups (p = 0.1606). Although cigarette smoking did not alter the underlying biology of breast tumors or breast cancer-specific survival, overall survival was significantly worse in smokers, highlighting the importance of smoking cessation in the recently diagnosed breast cancer patient

Artificial Neurons and Synapses Based on Al/a-SiNxOy:H/P+-Si Device with Tunable Resistive Switching from Threshold to Memory

As the building block of brain-inspired computing, resistive switching memory devices have recently attracted great interest due to their biological function to mimic synapses and neurons, which displays the memory switching or threshold switching characteristic. To make it possible for the Si-based artificial neurons and synapse to be integrated with the neuromorphic chip, the tunable threshold and memory switching characteristic is highly in demand for their perfect compatibility with the mature CMOS technology. We first report artificial neurons and synapses based on the Al/a-SiNxOy:H/P+-Si device with the tunable switching from threshold to memory can be realized by controlling the compliance current. It is found that volatile TS from Al/a-SiNxOy:H/P+-Si device under the lower compliance current is induced by the weak Si dangling bond conductive pathway, which originates from the broken Si-H bonds. While stable nonvolatile MS under the higher compliance current is attributed to the strong Si dangling bond conductive pathway, which is formed by the broken Si-H and Si-O bonds. Theoretical calculation reveals that the conduction mechanism of TS and MS agree with P-F model, space charge limited current model and Ohm’s law, respectively. The tunable TS and MS characteristic of Al/a-SiNxOy:H/P+-Si device can be successfully employed to mimic the biological behavior of neurons and synapse including the integrate-and-fire function, paired-pulse facilitation, long-term potentiation and long-term depression as well as spike-timing-dependent plasticity. Our discovery supplies an effective way to construct the neuromorphic devices for brain-inspired computing in the AI period